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dict
validate_training
bool
val_split_mode
string
val_data_root
null
val_split_proportion
float64
stabilize_training_loss
bool
stabilize_split_proportion
float64
every_n_epochs
int64
seed
int64
{ "validate_training": "If true, validate the training using a separate set of image/caption pairs, and log the results as `loss/val`. The curve will trend downwards as the model trains, then flatten and start to trend upwards as effective training finishes and the model begins to overfit the training data. Very usef...
true
automatic
null
0.15
true
0.15
1
555
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